Research Scientist Positions
We are looking for research scientists to conduct novel research in AI for healthcare at IHU Strasbourg/University of Strasbourg in the areas of medical image analysis, computer aided surgery and surgical data science. More information is available here.
PhD and Post-doctoral Positions
In the context of the national AI Chair project AI4ORSafety, which aims at developing new AI methods for automating the assessment of critical safety steps during surgery, we are currently looking for two PhD students and one post-doctoral fellow in Computer Vision/Artificial Intelligence:
(1) Phd position: Federated Learning for Scaling-up Surgical Activity Analysis
(2) Phd position: Self-supervision for Anatomy and Activity Recognition in Endoscopic Videos
(3) Post-doctoral position: AI Methods for the Automated Assessment of Critical Safety Steps in Surgery
Internships
We are offering several internship positions / Master’s theses for motivated students interested in contributing to the development of our computer vision system for the operating room. Knowledge in computer vision or machine learning is expected. If you are interested in doing an internship in one of the areas listed below, please send Nicolas Padoy a short email including a description of your interests and a resume. All positions are funded and have a duration from 5 to 6 months. Successful candidates will be hosted within the IHU institute at the University Hospital of Strasbourg. He/She will thereby have direct contact with clinicians and also have access to an exceptional research environment.
Topics:
| Deep Learning for Activity Recognition in Large Surgical Video Databases | |
 | Develop an approach to model, detect and recognize the surgical activities occurring within the hundreds of videos from our constantly growing surgical database. The approach will focus either on endoscopic videos or on multiple external RGBD views capturing the clinicians' activities. It will also be integrated into our live demonstrator for the operating room. |
| Multi-view Human Body Tracking for the Operating Room | |
 | Design a robust method to estimate the 3D body poses of clinicians using a multi-RGBD camera system mounted directly in the operating room of our clinical partner. The approach will have to address several issues related to clutter, occlusions and temporal tracking. |
| 3D Visualization of X-ray Propagation for Radiation Safety Analysis | |
 | Propose a method for the intuitive visualization of the 3D radiation risk in the interventional radiology room using the Microsoft HoloLens head-mounted display. The method will rely on our ceiling-mounted multi-RGBD camera system and be implemented on GPU to enable quick interactions between the clinicians and the monitoring system. |
More details available upon request. Illustrative videos related to the projects are available here.